Assume your data distribution is x1; x2; :::; xnj(; 2) N(; 2). Assume the following priors on the parameters: N(0; 2 0), and 2 IG(a; b), where 0 = 2; 2 0 = 1; a = 1; b = 1 are fixed and known. (i) Derive the full posterior using the data likelihood and the prior, along with the full conditionals. Show your work in detail